1. Field of the Invention
The present invention relates to electronic computerized medical instruments and more particularly to the analysis and display of bioelectromagnetic signals of the brain and the heart for detecting abnormal functioning by a non-invasive computerized system and method.
2. Description of Related Art
Classical electroencephalography (EEG) and electroencephalography (EKG) are techniques for the diagnosis of of brain and heart dysfunctions that have been demonstrated to be useful for a number of decades. These methods are largely based on the skill, memory, and experience of a neurologist or cardiologist that examines tracings of bioelectric activity recorded upon paper. Recently, biomagnetic measurements of both the heart and brain have been introduced for the same purposes. Thus, a patient may be examined with any of the following techniques that yield information about current source generators in the human body: electroencephalography (EEG), magnetoencephalography (MEG), brain evoked response (ER), electrocardiography (EKG), and magnetocardiography (MKG).
In recent years computerized techniques for recording, analyzing and visually displaying electromagnetic signals of the brain and the heart have been introduced, in an attempt to achieve greater objectivity in diagnostic procedures as well as uncovering subtle dysfunctions otherwise difficult to detect except by a highly trained specialist.
The current state of the art, as reflected in U.S. Pat. Nos. 4,417,592; 4,421,122; 4,913,160; and 4,974,598 is as follows:
a) Selected features of the electromagnetic signals of a patient are extracted by means of different data transforms, amongst which the most prominent are: no transform (working with the raw data), broad band spectral analysis, and the Karhunen Loeve expansions.
b) These features are subjected to statistical comparison with standards extracted from a database of normal subjects.
c) As a final result, topographic maps are displayed of the head and torso (for brain and heart data respectively) in which the intensity of deviation from the norm are color-coded in terms of univariate statistical distributions.
There is abundant evidence (Valdes et al., QEEG in a public health system, Invited lecture at the 2d Congress of Brain Electromagnetic Topography, Brain Topography, 1991, in press) that these procedures are clinically useful in both specialized medical care as well in public health facilities. In spite of these promising results the sensitivity and specificity of these procedures has been limited to date by a number of factors that include:
i) The feature sets defined to date are too large, presenting multiple multivariate statistical colinearities. Thus, problems arise as to the definition of probability scales and the decision as to whether a deviation in a probability map is actually abnormal. Duffy et al. (Quantified Neurophysiology with Mapping: Statistical Inference, Exploratory and Confirmatory; Data Analysis, Brain Topography Vol. 3 No. 1, Fall 1990 pp. 3-12) have demonstrated the excessively high false positive rates created by this situation.
ii) The data transforms used to date, while useful in some situations, have been demonstrated (Valdes et al.,High Resolution Spectral EEG Norms for Topography, Brain Topography Vol. 3 No. 1, Fall 1990 pp. 281-282) to be too coarse to reconstruct the profile of many abnormalities.
iii) Topographic maps and curves of features are constructed without taking into consideration the high correlation of features due to biological constraints being in fact univariate projections of patient data in which the abnormalities may be multivariate.
iv) Topographic maps and curves representing a vector of features are currently color-coded only using the marginal (univariate) probability distribution of each component of the vector. This increases the probability of false positive findings when searching for significant regions in the whole map or curve.